the Lisp compiler to JavaScript, written in JavaScript, following the workflow of TDD (Test-Driven Development). All is “work in progress”, so today I will explain part of the implementation but it could be change in the future, when new use cases were added, and new ways of doing things were implemented.

I took the decision that each Lisp symbol is a JavaScript variable. So, the compilation of a symbol is:

The implementation of a Lisp is a good programming exercise. Lisp is a simple and powerful language, with functions as first class citizens. And with the “twist” of implementing functions that don’t evaluate their arguments, and macros.

This time, I want to implement a Lisp, but as a compiler. I started to write a Lisp compiler in JavaScript, that generates JavaScript. The project:

As usual, I worked using the Test-Driven Development workflow. With simple use cases, I implemented the needed features. This is my first Lisp compiler, so I’m trying new implementation approaches. I know Clojure, as a basis for a Lisp compiler. I should implement:

Symbols: identifiers witn name and associated value. Now, I’m compiling them to JavaScript variables. In SimpleLisp, a symbol can be defined at top, in a let block, or as a function argument. Then, I produce a top variable (or a least, a module variable), or a local variable in let, or an argument in function.

Functions: I’m translating a normal function in Lisp to a normal function in JavaScript. The main difference is that Lisp functions returns a value, there are no commands, all are expression, as in Ruby. A list in SimpleLisp is then compiled to a function call in JavaScript.

Special Forms: Their implementation is a novelty to me. In a compiler, I could generate directly the final code for each list with a head that is an special form. So, I’m compiling directly to JavaScript any list with head if, do, let, etc… . A list (if ….) is compiled to a JavaScript if, but returning a value.

Macros: In a compiler, I could adopt a new implementation: to expand the macro at COMPILING TIME. I’m not sure yet if I can take this approach in every case. Notably, in Clojure a macro is not a functional value: a macro cannot be passed as an argument. A macro make sense only at compiling time.

A final use case: write a web site using Node.js/Express in SimpleLisp.

RMoD http://rmod.inria.fr/web/The goal of RMoD is to support remodularization of object-oriented applications. This objective is tackled from two complementary perspectives: reengineering and modularity constructs for programming languages.

July 27, 2014

Year and a half since I didn’t write about this project in C #, but I was working on it, and the parallel implementation I have in JavaScript (in fact, I introduced some concepts of both the Smalltalks 2013 conference, Rosario, Argentina).

It can compile to bytecodes or to JavaScript. The project is written in JavaScript.

The window implementation is very primitive. I plan to replace it for direct AjTalk program using .NET types and object.

One point that I find very interesting (in both projects, C # and JavaScript) is to have a modular implementation: instead of loading an image yet defined, my plan is to define modules to load, as happens in the Node.js environment . The modules would be published in the NPM (Node Package Manager’s), and each could indicate which modules need in your program instead of lifting all Smalltalk.

Another topic in this C # project I have implemented that can run more than one AjTalk machine at the same time. And I can even make a machine “help” to the other. For example, if the machine does not have to compile methods to new methods, machine B can go to his aid. Thus, A machine (and his image, I’m already recording binary image) can be kept small.

Another feature that I have implemented: the ability to send a message to an object, without waiting for a response, a “fire and forget”. And that the target object can attend ONE OF those messages as models of actors.

I have to review the implementation of remote objects (now based on the old Remoting. NET). But I think it is an important feature to maintain and explore.

Well, you see, many issues remain for other posts, such as implementation details Smalltalk concepts such as Object, Class, ClassDescription, Behavior, MetaClass, etc..

July 22, 2014

Since the past decade I’m interested on Clojure. It’s a return to Lisp, but in modern times.. Clojure is implemented on the Java virtual machine, but is also implemented on. NET (AFAIK, using Dynamic Language Runtime). The version of Java compiles to Java bytecodes. There is also a version of JavaScript, called ClojureScript. The community is very active, and has brought an air of renewal within Java. It has features like immutability of his work-oriented structures in multithreading, avoiding concurrency problems. It supports Software Transactional Memory, but has been less used by what I see. Web frameworks have emerged, and has a project and dependencies manager called Leiningen. Some links in my Clojure posts.

It has a class library project, and a test project. There is also a REPL (Read Eval Print Loop) simple console application.

In Lisp, an expressions is composed by a verb and arguments, written in a list enclosed by parenthesis. For example, a list that at evaluation returns the sum of 1, 2 and 3:

(+ 1 2 3)

Here, the plus + sign is a symbol that in Lisp/Clojure refers to a form. A form receives arguments, operates on them, and returns a result. A typical form receives its arguments as evaluated expressions: the expressions are evaluated BEFORE the evaluation of the form:

(+ 1 (- 3 4) 3)

In the above example, the first argument to plus is a constant 1, and the second argument is an expression that is evaluated to –1 before the evaluation of the outer list.

But there are forms that not need evaluated arguments. They receive the arguments without evaluation. They are called special forms. I have implemented:

And I have implemented some (non special) forms as primitives in C#. Most of them could be implemented in Lisp itself, but being so basic that I preferred to implement them directly in C#, using TDD as usual:

Next topics: the Machine implementation, Context, how to use Parser and Lexer, more about expression evaluation, macros, tail recursion, etc.

It is an interpreter (not a compiler) of Go programming language, written in C#. It has a class library project, and a test project. Go is a typed language, so I cannot follow the path of build an expression tree, and evaluate it, as in RubySharp, PythonSharp and Mass. Instead, the interpreter should have many phases, as in ScalaSharp, to detect type inconsistencies, and use the declaration of unknown types at the parse process.

The AST is implemented:

The AST (Abstract Syntax Tree) nodes are in two groups:

- Command Nodes, where they should generate commands to be executed.

- Expression Nodes, that generates expressions to be evaluated. They have an associated type.

The commands declare variables with types. By now, I have all in place to start:

- Declare the types of some declarations of variables and functions - Control that types are the right ones, ie, an integer variable should not be assigned to an string expression - Start to emit commands and expression

As in other projects, I want to add access to native .NET types, libraries and objects. I should research how many features of Go I could implement in this approarch. An example: the implementation of Go structures, and their original semantic in C#. I could implement channels (years ago, I implemented channels in C# and AjSharp).

A simple interpreter for a simplified Scala, C #. I do not intend to implement all Scala as a compiler for CLR. NET. My intention is to explore an alternative implementation of interpreter, adopting only some “light” features of Scala.

Without being a Scala programmer (or amateur or professional) my impression is that Scala as a language and library, is something like "too much", a bit overwhelming. People adopts Scala because it is more flexible, less need "boilerplate" etc.. But it seems like Scala went too far. Having programmed in Java and C#, I think the latter, adding a few things (delegates years, lambdas, extension methods, "generics" in the VM, and recently, in asynchronous input/output, async, await), has managed to stay healthy, without major complications. See how easy it has been to implement LINQ with evaluation "lazy" and others.

Instead, Scala seems to me like it’s too many things, all together. From what I saw, type inference is a feature that is not so necessary in the real projects. And yet I can not accept that the list of operators in Scala occupies more than one web page. But hey, that’s the current state of things. People Scala is working on a new implementation, called Dotty. But if you are just doing after years of language definition, I have to declare: "too little, too late."

That does not preclude recognizing that Scala has great triumphs, non-trivial applications like Play Framework and Akka. Akka is a very interesting project. I think we don’t need so many new language features (just the ones I mentioned for C #). We need more libraries that solve some issues (such as the implementation of an asynchronous HTTP message distribution server or distributed processing among actors).

To experiment with a simplified Scala, and to deliberately practice TDD (Test-Driven Development) in C #, I started the project ScalaSharp.

It is a challenge for me, because it is not a simple interpreter. I want to implement an AST (Abstract Syntax Tree) that detects inconsistencies between types. In my previous experiences, as RubySharp, PythonSharp, and Mass language, it was only necessary to assemble a tree expressions / commands and evaluate it. Now I’ll have to check that the types are correct. For example, one variable that is typed, and that their assignments, the expression to be evaluated and assigned for the type of the variable. You can see some of the work in progress:

Upcoming topics: implementation details, control types in the AST transformation commands / expressions. The good thing to do with TDD is that it allows me to go implemented the solution as I define use cases.

It receives the object to which it is a method, the context, and a list of arguments. Each of the arguments was evaluated. The implementation simply sends the arguments to a TextWriter, one argument per line. The TextWriter is provided when the function object is created (in the Machine object, that represents the current running environment). This injected facilites the test of the function, example: